代码工具 中山大学

General
mexopencv: collection and a development kit of matlab mex functions for OpenCV library. This software package provides matlab mex functions that interface a hundred of OpenCV APIs. Also the package contains a C++ class that converts between Matlab’s native data types and OpenCV data types. The package is suitable for fast prototyping of OpenCV application in Matlab, use of OpenCV as an external toolbox in Matlab, and the development of a custom mex function.

**STPRtool: **Statistical Pattern Recognition ToolboxThis toolbox implements a selection of statistical pattern recognition methods described in the monograph M.I. Schlesinger, V. Hlavac: Ten lectures on the statistical and structural pattern recognition, Kluwer Academic Publishers, 2002 , rather it implements the first part of the monograph which deals with feature based statistical pattern recognition methods. The toolbox is still being developed and new implemented methods (see implemeted methods) go beyond the contents of the monograph.

Inference
Max-flow/min-cut and Graph Cut
libDAI: A free and open source C++ library for Discrete Approximate Inference in graphical modelsCurrently, libDAI supports the following (approximate) inference methods:
Exact inference by brute force enumeration;
Exact inference by junction-tree methods;
Mean Field;
Loopy Belief Propagation [KFL01];
Fractional Belief Propagation [WiH03];
Tree-Reweighted Belief Propagation [WJW03];
Tree Expectation Propagation [MiQ04];
Generalized Belief Propagation [YFW05];
Double-loop GBP [HAK03];
Various variants of Loop Corrected Belief Propagation [MoK07, MoR05];
Gibbs sampler;
Conditioned Belief Propagation [EaG09];
Decimation algorithm.

These inference methods can be used to calculate partition sums, marginals over subsets of variables, and MAP states (the joint state of variables that has maximum probability).
In addition, libDAI supports parameter learning of conditional probability tables by Expectation Maximization.

Detectors
Skin Detection (matlab).